Smartphone biosensor

ABSTRACT

A mobile computing device that includes an image sensor may be used to detect the result of a biomolecular assay. The biomolecular assay may be performed in an optical assay medium that provides an optical output in response to light from a light source, with the optical output indicating result. A wavelength-dispersive element may be used to disperse the optical output into spatially-separated wavelength components. The mobile computing device may be positioned relative to the wavelength-dispersive element such that different wavelength components are received at different locations on the image sensor. With the mobile computing device positioned in this way, the image sensor may be used to obtain one or more images that include the separated wavelength components of the optical output. A wavelength spectrum of the optical output may be determined from the one or more images, and the result may be determined from the wavelength spectrum.

PRIORITY

This application is a division of U.S. application Ser. No. 13/801,978filed Mar. 13, 2013, which claims priority under 35 U.S.C. §119(e) toU.S. Provisional Application No. 61/748,903 filed Jan. 4, 2013, and thecontent of which these applications is incorporated by reference herein.

BACKGROUND

Since their introduction in 1997, “smartphones” have gained rapid marketacceptance. Smartphones provide the user with advanced features inaddition to being able to make voice calls. For example, smartphonestypically have internet connectivity, high resolution cameras andtouch-screen displays, and powerful CPUs. The rapid acceptance ofsmartphones has been driven by a combination of falling prices andincreasingly sophisticated features. In addition, there is a growingecosystem of applications that take advantage of smartphones' sensors,displays, and ability to connect to powerful computing and data storagecapabilities that are available in the “cloud.” The built-incapabilities of smartphones can be further extended through the additionof accessories that enable the phone to sense different types ofinformation. For example, it is already possible to find commercial lenssystems that enable the phone to be used as a rudimentary microscopewith a 350× magnification, which is sufficient for capturing images ofcells, bacteria, and biological tissue. Breslauer et al., Plos One, vol.4, Jul. 22, 2009 and Smith et al., Plos One, vol. 6, Mar. 2, 2011. Smithet al. also demonstrated that, with addition of a light collimationsystem and a diffraction grating in front of the camera, a smartphonemay function as a spectrometer with a wavelength resolution of 5 nm. Theability of a smartphone camera to take images of the colored labelcomponents of a biological assay have been applied to lateral flowimmunoassays (Mudanyali et al., Lab Chip, vol. 12, pp. 2678-86, 2012),quantum-dot labeling of bacteria (Zhu et al., Analyst, vol. 137, pp.2541-2544, 2012), and fluorescence microscopy (Breslauer et al.).Further, smartphone cameras have recently been exploited formicrofluidic and optofluidic applications (Martinez et al, AnalyticalChemistry, vol. 80, pp. 3699-3707, May 15 2008 and Zhu et al.,Analytical Chemistry, vol. 83, pp. 6641-6647, Sep. 1, 2011) and as alens-free microscopy tool (Tseng et al., Lab on a Chip, vol. 10, pp.1787-1792, 2010).

Such approaches, however, have not involved biomolecular assays withlabel-free detection. Detection of an analyte through one of itsintrinsic physical properties (e.g., dielectric permittivity, mass,conductivity, or Raman scattering spectrum), called “label-free”detection, can be preferable for assay simplicity in terms of the numberof reagents required, washing steps needed, and assay time. Of all thelabel-free detection approaches that have been demonstrated, those basedupon optical phenomena have been most commercially accepted due to acombination of sensitivity, sensor cost, detection system robustness,and high throughput. Adsorption of biomolecules, viral particles,bacteria, or cells on the surface of an optical biosensor transducerresults in a shift in the conditions of optimal optical coupling, whichcan be measured by illuminating the transducer surface, and subsequentlymeasuring a property of the reflected or transmitted light. Such adetection approach is extremely robust, and has become economicallyadvantageous due to the advent of low cost light emitting diodes (LEDs),semiconductor lasers, and miniature spectrometers. For example, surfaceplasmon resonance (SPR) based biosensors and photonic crystal (PC)optical biosensors are capable of detecting broad classes of biologicalanalytes through their intrinsic dielectric permittivity. Each approachhas been implemented in the form of large laboratory instruments andminiaturized (shoebox-sized) systems. However, no prior label-freeoptical biosensor instrument has been fully integrated with asmartphone, using the camera in the phone itself as the detectioninstrument.

SUMMARY

In a first aspect, example embodiments provide a system comprising alight source, an optical assay medium configured to perform abiomolecular assay and provide an optical output in response to lightform the light source, wherein the optical output is indicative of aresult of the biomolecular assay, a wavelength-dispersive element, and amobile computing device. The wavelength-dispersive element is configuredto disperse the optical output into spatially-separated wavelengthcomponents. The mobile computing device includes an image sensorconfigured to receive at least a portion of the dispersed optical outputsuch that different wavelength components are received at differentlocations on the image sensor.

The light source could be a broadband light source, such as anincandescent light bulb, sunlight, or an LED (either an LED on thesmartphone or an external LED). Alternatively, the light source could bea narrow-band light source, such as a laser.

The wavelength-dispersive element could be a diffraction gratingconfigured to diffract the optical output into at least one diffractionorder in which different wavelength components of the optical outputhave different diffraction angles. Other types of wavelength-dispersiveelements could also be used.

The system could include a mount for removably mounting the mobilecomputing device in a predetermined position relative to thewavelength-dispersive element and/or other optical components. Themobile computing device could be a smartphone, handheld computer, tabletcomputer, or other easily portable computing device. In some examples,the mobile computing device includes a display, a processor, a memory,and program instructions stored in the memory and executable by theprocessor to cause the mobile computing device to perform functions,such as: (i) using the image sensor to obtain at least one image of thespatially-separated wavelength components; (ii) determining a wavelengthspectrum of the optical output based on the at least one image of thespatially-separated wavelength components; and (iii) displaying anindication of the wavelength spectrum on the display. The functionscould further include determining the result of the biomolecular assaybased on the wavelength spectrum and displaying an indication of theresult on the display.

In some embodiments, the optical assay medium could include a photoniccrystal (PC). The optical output could include light from the lightsource transmitted through the PC, with a wavelength spectrum having alocal minimum in a range of wavelengths resonantly reflected by the PC.Alternatively, the optical output could include light from the lightsource reflected from the PC, with a wavelength spectrum having a localmaximum in a range of wavelengths resonantly reflected from the PC. Ineither approach, the wavelengths that are resonantly reflected from thePC could be indicative of the result of the biomolecular assay.

In some embodiments, the optical assay medium could be configured toperform an optical absorption assay. For example, the optical assaymedium could include a transparent container containing a compositionfor performing an enzyme-linked immunosorbent assay (ELISA) thatproduces a colored product in the presence of an analyte. Thus, theoptical output could include light from the light source transmittedthrough the container, with a wavelength spectrum having an absorptionfeature related to absorption of light by the colored product. Theintensity of the absorption feature could be indicative of the result ofthe biomolecular assay.

In some embodiments, the optical assay medium could include afluorophore for performing a fluorescence assay. Thus, the opticaloutput could include fluorescence emission from the fluorophore that isexcited by light from the light source. The intensity of thefluorescence emission could be indicative of the result of thebiomolecular assay. The fluorophore could be proximal to a surface, suchas a photonic crystal, such that the fluorescence emission is enhanced.The optical assay medium could also include multiple fluorophores, suchas a donor fluorophore and an acceptor fluorophore. Thus, the opticaloutput could include fluorescence emission from the donor fluorophoreand/or acceptor fluorophore that is excited by light from the lightsource. The intensity of the fluorescence emission from the donorfluorophore and/or acceptor fluorophore could be indicative of theresult of the biomolecular assay.

In some embodiments, the optical assay medium could include afluorophore for performing a fluorescence polarization assay. In suchembodiments, the light source could be polarized, such as by using aninherently polarized light source or an unpolarized light source inconjunction with a polarizer. The optical output could includefluorescence emission from the fluorophore that is excited by light fromthe light source. The polarization of the fluorescence emission isindicative of the result of the biomolecular assay. To measure thepolarization, the fluorescence emission could be passed through apolarizer that can be adjusted between two orthogonal polarizations, andthe intensity of the fluorescence emission could be measured at the twoorthogonal polarizations of the polarizer.

In some embodiments, the optical assay medium could include a surfaceconfigured for surface-enhanced Raman scattering (SERS). Thus, theoptical output could include Raman scattering of the light source bymolecules proximal to the SERS surface. The intensity of the Ramanscattering could be indicative of the result of the biomolecular assay.

In a second aspect, example embodiments provide a method. The method mayinvolve the following: performing a bimolecular assay in an opticalassay medium; exposing the optical assay medium to light from a lightsource to produce an optical output, wherein the optical output isindicative of a result of the biomolecular assay; dispersing the opticaloutput into spatially-separated wavelength components; using an imagesensor of a mobile computing device to obtain at least one image of atleast a portion of the dispersed optical output; and determining theresult of the biomolecular assay based on the at least one image. Theresult of the biomolecular assay could be determined by the mobilecomputing device by determining a wavelength spectrum of the opticaloutput based on the at least one image and determining the result of thebiomolecular assay based on the wavelength spectrum.

The method may further involve placing the optical assay medium in asample chamber of an instrument, wherein the instrument includes aninput optical path for directing light from the light source to theoptical assay medium in the sample chamber and an optical output pathfor receiving the optical output from the optical assay medium in thesample chamber. The mobile computing device could be removably mountedto the instrument. Mounting the computing device to the instrument couldinvolve optically coupling the image sensor of the mobile computingdevice to the optical output path. Mounting the computing device to theinstrument could further involve coupling a light source on the mobilecomputing device, such as an LED, to the input optical path. Thus,exposing the optical assay medium to light from a light source couldinvolve exposing the optical assay medium to light from the light sourceon the mobile computing device.

In a third aspect, example embodiments provide an optical instrument.The optical instrument comprises a sample chamber for receiving anoptical assay medium, an input optical path for directing light from alight source to the optical assay medium in the sample chamber, anoutput optical path for receiving an optical output from the opticalassay medium in the sample chamber, and a mount for removably mountingthe mobile computing device to the instrument in a working position. Inthe working position, an image sensor of the mobile computing device isoptically coupled to the optical output path.

The optical output path could include a diffraction grating configuredto disperse the optical output into spatially-separated wavelengthcomponents. Thus, with the mobile computing device in the workingposition, the image sensor may receive at least a portion of thedispersed optical output such that different wavelength components arereceived at different locations on the image sensor. In addition, alight source on the mobile computing device (such as an LED) may beoptically coupled to the input optical path when the mobile computingdevice is in the working position.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a cross-sectional schematic view of an example photoniccrystal (PC) structure.

FIG. 1B is a diagram that illustrates the operating principle of a PCaccording to an example embodiment.

FIG. 2A is a schematic diagram showing the optical components of anexample smartphone detection system.

FIG. 2B is a diagram showing a view of an example cradle with asmartphone mounted thereto.

FIG. 3A is a diagram showing another view of the cradle of FIG. 2B.

FIG. 3B is a diagram showing the internal optical components of thecradle of FIG. 2B.

FIG. 4A shows an example wavelength spectrum as it may be displayed on asmartphone.

FIG. 4B is a graph of the wavelength spectrum of FIG. 4A.

FIG. 5 is a block diagram of an example mobile computing device.

FIGS. 6A-6E show screen views of an example smartphone application.

FIG. 7 shows spectra from a red laser pointer, a green laser pointer,and a tungsten lamp, as measured by a spectrometer and by a smartphone.

FIG. 8 shows 13 independent PC spectra.

FIG. 9 shows normalized transmission characteristics for a bare PC andfor an adjacent region of the same PC coated with a 20 nm SiO₂ film.

FIG. 10 shows transmission spectra of a PC before and after depositionof a monolayer of PPL protein.

FIG. 11 is a graph showing the shift in PC resonant wavelength as afunction of concentration of an oligonucleotide.

FIG. 12 is schematic diagram of a smartphone mounted to an examplefixture for measuring reflection spectra from a PC.

FIG. 13 is a schematic diagram illustrating an example of using asmartphone for detection of an ELISA assay.

FIG. 14 is a schematic diagram illustrating an example of using asmartphone for detection of a surface-based fluorescence assay.

FIG. 15 is a schematic diagram illustrating an example of using asmartphone for detection of a fluorescence polarization assay

FIG. 16 is a schematic diagram showing a smartphone mounted to anexample multimode instrument.

DETAILED DESCRIPTION 1. Overview

A mobile computing device (e.g., a smartphone) that includes an imagesensor can be used as the detection instrument for various types ofbiomolecular assays. Such biomolecular assays may involve thequalitative or quantitative detection of DNA, RNA, nucleotides,proteins, or any other biologically relevant molecules. In an exampleembodiment, the mobile computing device is mounted to a special-purposecradle that holds one or more optical components in alignment with theimage sensor. With the mobile computing device properly mounted, theimage sensor can be used to obtain one or more images from which thewavelength spectrum of an optical output of a biomolecular assay can bedetermined. In this way, the image sensor of a mobile computing devicecan perform the function of a high resolution spectrometer andwavelength filter.

The biomolecular assay may be performed in an optical assay medium thatis illuminated using either a light source on the mobile computingdevice, such as a light emitting diode (LED), or an external lightsource, such as a light bulb, LED, or laser. In response to thisillumination, the optical assay medium provides an optical output with awavelength spectrum that can be detected by the image sensor on themobile computing device. For example, a diffraction grating or otherwavelength-dispersive element may be used to disperse the optical outputinto spatially-separated wavelength components such that differentwavelength components are received at different locations on the imagesensor.

In some embodiments, the optical assay medium may include a label-freeoptical biosensor, such as a photonic crystal biosensor, resonantwaveguide grating biosensor, surface plasmon resonant biosensor, orother type of optical biosensor. In some embodiments, the optical assaymedium may include a fluorophore or multiple fluorophores (e.g., a donorfluorophore and an acceptor fluorophore) for performing a fluorescentassay. The fluorescent assay could be either homogenous (e.g., afluorescence polarization assay) or surface-based. For example, theoptical assay medium may include a surface, such as a photonic crystal,that enhances the fluorescence output. Liquid-based fluorescent assayscould also be used to detect fluorescence resonance energy transfer(FRET), fluorescent particles (e.g., microparticles or nanoparticles),or fluorescent molecular beacons. In some embodiments, the optical assaymedium may include a composition for performing an optical absorptionassay, such as an enzyme-linked immunosorbent assay (ELISA). In someembodiments, the optical assay medium may include a surface forperforming surface-enhanced Raman scattering. The optical assay mediumcould perform other types of assays as well.

The use of a smartphone or other mobile computing device as thedetection instrument for biomolecular assays allows expensive, portable,and multifunctional systems to perform biosensor assays in contextsoutside the laboratory. Applications can include point-of-carediagnostic systems for measuring viral loads, nutritional status,disease biomarkers, or environmental contaminants in contexts wherelaboratory-based detection instruments are not possible. Such testscould be performed in the home, in global-health settings, in lawenforcement and in clinics. The mobile computing device can also provideinternet connectivity that allows sensor data to be easily combined withpatient information and geographical location. and interfaced with anexternal computation facility that can perform functions like datainterpretation, mapping (for example, measuring the distributedcharacteristics of a population or a natural resource), construction ofdatabases, and alerting of a remotely located medical expert forimmediate feedback to the patient. Smartphone-based biosensor assays canallow tests that are currently only performed by trained technicians inlaboratories to be performed by anyone by reducing the size and cost ofthe detection system.

2. Example Photonic Crystal Biosensors

Photonic crystal biosensors are described in U.S. Pat. Nos. 7,479,404,7,521,769, 7,531,786, 7,737,392, 7,742,662, and 7,968,836, which patentsare incorporated herein by reference. In general, a photonic crystal(PC) includes a thin film of a material with a high index of refractionon a one-dimensional or two-dimensional grating structure that is formedin a material with a low index of refraction. The grating dimensions,thin film thicknesses, and indices of refraction can be selected so thatthe structure behaves as a high efficiency narrowband reflectance filterwith a resonance having a center wavelength and a resonance bandwidth.

FIG. 1A illustrates an example PC. In this example, a 1-dimensionalgrating structure is formed in a UV-curable polymer (UVCP) on a flexibleplastic substrate (PET) by a nanoreplica molding process. The gratingperiod is 360 nm and the grating depth is 60 nm. The polymer grating isover-coated with sputtered thin films of SiO₂ (200 nm thickness) andTiO₂ (60 nm thickness, refractive index=2.35). After fabrication, theflexible plastic substrates of one or more PCs can be attached to acarrier, such as a glass microscope slide, using double-sidedpressure-activated adhesive film. In this way, a standard 1 inch×3 inchglass microscope slide can accommodate multiple PCs (e.g., 21 PCs in a3×7 array).

Depending on the structure of the PC, the center wavelength could be inthe infrared, visible, or ultraviolet. With the center wavelength at 565nm, the resonance bandwidth could have a full width at half maximum(FWHM) of about 5 nm. The narrow band of resonantly reflectedwavelengths could be reflected with over 95% efficiency. As a result,when the PC is illuminated by collimated light at normal incidence, allwavelengths may pass through the PC with little or no attenuation,except for the narrow band of resonantly reflected wavelengths. Thisprinciple is illustrated in FIG. 1B, which shows a transmission spectrumwith a sharp dip that corresponds to the narrow band of resonantlyreflected wavelengths. Adsorption of materials, such as biomolecules,viral particles, bacteria, or cells, on the PC surface results in anincrease of the effective refractive index of the resonant mode. Thiscreates a positive shift in the wavelength of resonant reflection, themagnitude of which is proportional to the optical density of theadsorbed material. Therefore, a measurable shift of the peak wavelengthvalue (PWV) of minimum transmission efficiency (or equivalently amaximum in reflection efficiency) can occur as a result of a biologicalassay.

3. Example Smartphone Cradle Optical System

FIG. 2A is a schematic diagram illustrating an example detection system100 that includes a smartphone 102 with a digital camera. As shown inFIG. 2A, the digital camera includes a camera lens 104 and an imagesensor (CCD) 106. Unpolarized light from a broadband light source 108(such as an incandescent lamp, LED, or sunlight) passes through apinhole 110 (diameter=100 microns), a collimator 112 (a lens with afocal length of 75 mm), and a linear polarizer 114, so as to be incidentupon a photonic crystal (PC) 116 mounted to a glass microscope slide.The linear polarizer 114 is oriented to pass only light with itselectric field vector perpendicular to the grating lines in PC 116. Thecollimated and polarized light passes through the PC 116 at normalincidence, so all the incident light may pass forward, with theexception of the PC resonant wavelength band. A slot for the PC 116 canbe incorporated into the optical chain, to facilitate its insertion andremoval. Small markings can be made on the PC slide, so a specificlocation can be re-measured during distinct steps in the assay process.After passing through the PC 116, the light is focused to a line by acylindrical lens 118 (focal length=50 mm), onto the entrance pupil ofthe smartphone's camera. A diffraction grating 120 (1200 lines/mm)placed between the cylindrical lens and the camera disperses thewavelength components of the light across the camera's image sensor (CCD106). In this example, the optical path is set at an angle of ˜47° withrespect to the camera face so that the camera receives the grating'sfirst order.

To position the smartphone 102 so that its digital camera receives thefirst order of the diffraction grating 120, the smartphone can beremovably mounted to a cradle. FIGS. 2B, 3A, and 3B illustrate anexample cradle 150 that could be used. FIG. 2B is a side view of thecradle 150 with a smartphone 152 mounted thereto. In this example,smartphone 152 is an iPhone 4 (Apple, Inc.). It is to be understood,however, that other smartphones or other types of mobile computingdevice could be used. The cradle 150 shown in FIG. 2B was made ofanodized machined aluminum. Alternatively, the cradle 150 could be madeof injection molded plastic or other structural materials. The cradle150 includes a mounting portion 154 for mounting the smartphone 152 andalso includes a light-sealed optical housing 156 that houses opticalcomponents.

FIG. 3A shows the mounting portion 154 in more detail. The mountingportion 154 includes a recess 155 into which smartphone 152 can befitted. The smartphone 152 may be secured in place in recess 155 throughthe use of mounting screws 158. Smartphone 152 is mounted in recess 155with its user interface 159 facing out, as shown. Thus, in the mountedposition, user interface 159 (which includes a display and a touchscreeninterface) is accessible and smartphone 152 can be operated, forexample, to obtain images using its image sensor. The image sensor is onthe underside of smartphone 152 and, thus, is not shown in FIG. 3A.

FIG. 3B shows the back of cradle 150 with the light seal of opticalhousing 156 removed to show the optical components housed therein. Inthis example, the optical components are as described above for FIG. 2A,except that an external light source is used. Thus, light from theexternal light source enters cradle 150 through a pinhole 160 and thenpasses through a collimator 162, a polarizer 164, a PC 166 (mounted on aglass slide), a cylindrical lens 168, and a diffraction grating 170. Thelight in the first order of diffraction grating 170 enters recess 156through a hole 172 to reach the image sensor on the smartphone 152.

When the pinhole 160 is illuminated with light from a broadband source(e.g., a tungsten incandescent lamp) with PC 166 removed, the broadbandlight is dispersed by diffraction grating 170 and appears in a digitalimage obtained by smartphone 152 as a spectrum band that includes theentire visible spectrum (i.e., wavelengths from about 400 nm to about650 nm) in a “rainbow” type pattern. FIG. 3A shows an example spectrumband 174 (not shown in color) displayed on user interface 159 ofsmartphone 152. Although the iPhone4 image sensor has a total of 5megapixels (2592×1936), the spectrum band covers approximately 800pixels in the dispersive direction. With a pinhole 160 of approximately100 microns, the cylindrical lens 168 produces a focused line with awidth of roughly 100 pixels for each wavelength. Assuming a focal lengthof the iPhone4 lens of 4.3 mm, the wavelength separation betweenadjacent pixels in the spectral direction will be about 0.34 nm/pixel.

When PC 166 is inserted into the optical path, a narrow band ofwavelengths corresponding to the wavelengths resonantly reflected by PC166 is removed from the transmitted light, resulting in a dark band thatcan be observed in the spectrum band. FIG. 4A illustrates an examplespectrum band 200 that includes a dark band 202 resulting from resonantreflection from a PC. FIG. 4B is a graph 204 showing the variation inintensity (corresponding to transmission efficiency through PC) in thespectrum band 200 along the dispersive direction. The graph 204 clearlyshows a sharp dip 206 in the transmission efficiency that corresponds tothe dark band 202 that can be observed in the spectrum band 200. Withappropriate calibration, the pixel indices in the graph 204 can becorrelated to wavelengths, so as to enable determination of the peakwavelength value (PWV) of the dip 206.

4. Example Mobile Computing Device

FIG. 5 is a block diagram illustrating an example mobile computingdevice 300. The mobile computing device 300 could be a smartphone, ahandheld computer, a tablet computer, or other easily portable computingdevice. The mobile computing device 300 includes a communicationinterface 302 for wireless communication via an antenna 304. Thewireless communication could involve sending or receiving voice, images,video, data, or other information. The wireless communication could useany type of wireless communication protocol, such as 3G or 4G cellularcommunication protocols, WiFi, or Bluetooth. Instead of or in additionto communication interface 302, the mobile computing device 300 mayinclude a communication interface for communicating over USB, Ethernet,or other wired connections.

The mobile computing device 300 also includes a display 306 that candisplay text, images, graphics, or other visual information. A user mayinteract with the mobile computing device 300 via a user interface 308.The user interface 308 may include a touchscreen over the display 306.Alternatively or additionally, the user interface 308 may include akeypad, buttons, or other controls.

The mobile computing device 300 is able to capture still images and/orimages through the use of a camera 310. The camera 310 includes a lensand an image sensor, such as a CCD. The camera 310 could be on a side ofthe mobile computing device 300 that is opposite the side that includesthe display 306. The mobile computing device 300 may also include alight source, such as a white-light LED 312, next to the camera 310. TheLED 312 may be intended for flash photography, for example.

The mobile computing device 300 may be controlled by a controller 314that includes a processor 316 and a memory 318. The memory 318 couldinclude random access memory (RAM), read-only memory (ROM), flashmemory, or any other type of non-transitory media. The memory 318 maystore program instructions 320 and data 322. The processor 316 mayexecute the program instructions 320 to cause the mobile computingdevice 300 to perform functions, which functions may use or generatedata 322. The functions may involve communicating via the communicationinterface 302, displaying output on display 306, receiving user inputvia user interface 308, using camera 310 to obtain images, and/orcontrolling the illumination of LED 312. The program instructions 320may include software for one or more applications (often known as“Apps”) that can be accessed by a user.

5. Smartphone Biosensor Software App

An iPhone application (App) was developed to facilitate gathering ofspectra, measuring the PWV of the PC, and determining PWV shifts, usinga cradle such as cradle 150 described above. FIGS. 6A-6E are examplescreen views of the App. The App first prompts the user to enterinformation about a measurement, such as the sample name. Additionalglobal settings can be adjusted by the user to control filteringparameters, intensity threshold, and the span of pixels from the centerof the resonant band to be considered during curve fitting. To achievethe highest spectral resolution, the iPhone's camera is focused atinfinity. This can be done by pointing the camera to a distant object ina well lit environment before placing the iPhone into the cradle. TheApp locks the focal distance of the camera at infinity for allsubsequent measurements.

Tapping the “Capture” button within the App triggers the followingevents: A rapid sequence of spectra images (e.g., five spectra images)are captured consecutively to minimize the effects of small intensityfluctuations that arise from the light source and camera's sensor. Toobtain an intensity spectrum profile from each spectra image, the Appfirst crops the image to thirty pixels gathered from the center of the100-pixel wide spectral band, discarding dark pixels above and below theband. The 30 pixel values taken from the band are averaged to yield asingle intensity value for one wavelength of the spectrum for each ofthe consecutive images, resulting in a one dimensional array (1×2592pixels) per image captured. The spectra gathered from independentconsecutive images are finally averaged to yield a single spectrum. Thisprocess can take about two seconds. The App can also be calibrated tocorrelate pixel values with specific wavelength values.

The App stores the spectrum of the light source before a PC is insertedinto the cradle. The spectrum of the light source is used to normalizethe spectrum after the PC is inserted into the optical path to yield thePC transmission efficiency plot shown in FIG. 6E. It was found that thetransmission spectrum for the PC measured with the smartphone systemclosely matches the transmission spectrum obtained by illuminating thePC with the collimated output of an optical fiber and measuring thetransmission efficiency with a conventional spectrometer.

The App then processes the PC transmission spectrum to determine the PWVfor the measurement. The App identifies the pixel in the spectrum withthe lowest intensity value, and then uses the 20 pixel valuessurrounding this point to fit the “dip” to a third-order polynomialfunction. The PWV is mathematically determined as a local minimum of thepolynomial. In this way, PWV shifts ˜10× smaller than the wavelengthincrements of the camera can be measured. The App also enables wirelesstransmission of spectra and PWV measurements.

6. Example Measurements a. Measurement Protocol

Using the instrument (e.g., cradle 150 and smartphone 152) and software(e.g., the iPhone App described above), an assay can be performed asfollows. The PC is initially prepared with a capture molecule (such asan antibody, aptamer, or single-strand DNA sequence) that selectivelyrecognizes the analyte in a test sample. The sensor surface is furtherprepared with a “blocking” step that prevents nonspecific adsorption ofother molecules. The PWV of the sensor is measured prior to exposure tothe test sample to establish a baseline reading. Exposure of the sensorto the test sample results in adsorption of the analyte upon the PC,followed by rinsing/drying the sensor. A second PWV measurement is takenof the sensor, and the PWV shift is determined by subtraction of thebaseline PWV. The basic approach outlined here can be augmented by theincorporation of positive and negative experimental controls, includingthe use of a “reference” sensor that is prepared with an unmatchedcapture molecule, but still exposed to the test sample. Thus,measurements can be taken with the PC surface in a dry state.Alternatively, the system can be further augmented via incorporation ofa static liquid chamber or flow cell on the PC, so the PWV shifts can bemonitored kinetically.

b. Wavelength Calibration

Pixel values in the smartphone image were translated to calibrate thewavelength values through the use of two laser pointers and a calibratedspectrometer (Ocean Optics HR2000). As shown in FIG. 7, a green and ared laser pointer were used to illuminate the tip of an optical fiberwith its distal end connected to the spectrometer, resulting in thedashed curves with peak intensity values at wavelengths of λ=533.91 nmand λ=656.26 nm. The same laser pointers were then used to illuminatethe pinhole of the instrument (i.e., pinhole 160 in cradle 150),resulting in the solid curves shown in FIG. 7. Assuming linearitybetween the image pixel value and wavelength with two known values ofwavelength, it is possible to derive a transfer function that translatesevery pixel value into a wavelength value for all subsequentmeasurements. In this example, the index values in pixels are translatedinto a wavelength index through the conversion factor 0.334 nm/pixel.

Also shown in FIG. 7 is a comparison of the spectra from the tungstenlamp illumination source taken by the spectrometer and the smartphone. Adrop off in intensity is observed as the wavelength increases beyondλ=580 nm and a complete loss of sensitivity to wavelengths greater thanλ=680 nm can be attributed to an internal filter in the smartphone'scamera. Thus, the PC can be designed for operation in the 550<λ<580 nmrange in order to take advantage of the wavelengths available with goodsensitivity from the camera.

Using the pixel-to-wavelength mapping described above, the repeatabilityof independent PWV measurements, when the PC is removed/reinserted fromthe cradle without intentionally introducing any other variable, wasstudied. FIG. 8 shows 13 overlaid spectra from of independentmeasurements when the PC is removed and replaced within the cradle, aswould be the case when a biological assay is performed. The spectra areobserved to have a mean PWV=565.07 nm, and a standard deviation ofσ=0.10 nm, demonstrating that measurements are highly reproducible andthat wavelength shifts greater than 3σ=0.30 nm are statisticallymeaningful in the context of biological assays.

c. Example Measurements of PWV Shift

Shifts in the PC wavelength caused by addition of material to the PCsurface were measured as follows. A PC mounted to a microscope slide wasprepared by depositing a 20 nm thin film of SiO₂ by RF sputtering on onehalf of slide, while leaving the other half uncoated. Using a standardspectrometer, the PWV for the SiO₂ coated PC was measured and comparedto the bare PC region. A PWV difference of 5.08 nm was observed. Thetransmission spectra for the same regions of the PC were determinedusing the smartphone detection system. FIG. 9 shows the spectra for thebare PC and the SiO₂-coated PC. The PWV for the bare PC was 565.77 nm,and the PWV for the SiO₂-coated PC was 570.85 nm. Thus, a PWV shift of5.08 nm was measured using the smartphone detection system.

The PWV shift induced by adsorption of a protein monolayer on a PC wasalso measured. The protein polymer poly-phe-lysine (PPL) is well-knownto adhere to dielectric surfaces, such as the PC, forming a 15 nm thicklayer that self-limits to a single monolayer. A baseline spectrum from aspecific location of a PC biosensor slide in its “bare” state wasobtained. A temporary rubber gasket was then placed over that locationto create a liquid-containment well. The well was filled with 100 μL ofPPL (Sigma Aldrich) diluted in deionized water at a concentration of ˜1mg/ml, and allowed to incubate with the PC surface for 120 minutes atroom temperature. After incubation, the PPL solution was removed and thewell was flushed with deionized water. The gasket was removed, and thePC was further rinsed and dried with dry N₂ before returning the PC tothe detection system for a second spectral measurement. Results of thisexperiment are shown in FIG. 10. The PWV for the bare PC was 565.02 nm,and the PWV for the PC with the PPL monolayer was 566.68 nm. Thus, a PWVshift of 1.66 nm was observed.

d. Example Biodetection

In an example biodetection experiment, an immobilized molecule on a PCsurface is used to capture a molecule that is selectively recognized. Asa representative example, the smartphone detection instrument was usedto detect binding of a single-strand oligonucleotide sequence (20-mer)to an immobilized strand of its complementary sequence.

A PC mounted to a microscope slide was functionalized with anepoxysilane using a vapor deposition process as described below.Initially, the slide was washed in isopropanol and deionized (DI) waterfor two minutes, respectively. The PC was then dried under a stream ofnitrogen (N₂) and subjected to a 100 Watt oxygen (O₂) plasma for 10minutes at a pressure of 0.75 mTorr. Next, a vapor-deposition of3-glycidoxypropyltrimethoxysilane (Gelest, Inc.) was performed in a 500ml glass staining dish by transferring 100 μl of the silane to the dishand then placing a glass rack loaded with the device inside the dish.The dish was placed overnight in a vacuum oven at a temperature of 80°C. and a pressure of 30 Torr. The slide was then removed from the glassrack and sonicated in vertical staining jars of toluene, methanol and DIwater for two minutes each and finally dried under a stream of nitrogen(N₂). Three squares, each 9×9 mm² in dimension, were drawn on the slideusing a hydrophobic pen (Super HT Pap pen, Research ProductsInternational Corp), forming “wells” A to C. The spectrum of each wellwas recorded at this stage, and considered as the baseline of thisexperiment with an average PWV of 568.41 nm across all wells. Next, 100μL of the amine-modified, capture oligonucleotide (IDT, Inc.), preparedat a concentration of 2 μM in 3× saline sodium citrate (SSC) buffer(Sigma Aldrich) was applied to each well and incubated overnight. Thesequence of the capture oligonucleotide was 5′-/AminoModifier/ATT-TCC-GCT-GGT-CGT-CTG-CA-3′.

After the incubation period, the PC was rinsed first in a solution of DIwater with 0.2% by volume of SDS (Sigma Aldrich), followed by two rinsesin DI water. The PC was then dried in a stream of N₂ and PWV readingswere performed again on all wells. An average PWV of 577.53 nm wasobserved across the wells. Next, the complementary targetoligonucleotide (IDT, Inc.) was applied to the PC in equal volumes of100 μL per well but at three different concentrations of 1 μM (well A),750 nMm (well B) and 250 nMm (well C). A negative control well with notarget DNA was also created to record any non-specific shift. The targetoligonucleotide sequence used was 5′-TGC-AGA-CGA-CCA-GCG-GAA-AT-3′. Alldilutions were prepared using a 3×SSC buffer. Following an overnighthybridization of the target sequence, the PC was first rinsed in a 3×buffer solution and then rinsed twice in DI water. The PC was driedunder N₂ and the final spectrum in each well was recorded.

FIG. 11 shows the PWV shifts (ΔPWV values) that were measured for theconcentrations of 1 μM (well A), 750 nMm (well B) and 250 nMm (well C),as well as a negative control well with no target DNA. The PWV shiftswere found to be concentration dependent, generally increasing as afunction of increasing concentrations of the target DNA. The standarddeviations bars for each concentration in FIG. 11 represent the range ofΔPWV values obtained from measurements taken from two separate locationsin each well, representing nonuniformity in the assay process, ratherthan the noise of the sensor itself.

7. Example Smartphone Fixture for Measuring Reflection Spectra

While FIGS. 2A and 2B illustrate an arrangement in which a smartphonedetects a spectrum of light transmitted through a PC, it is alsopossible to use a smartphone to detect a spectrum of light reflectedfrom a PC. FIG. 12 illustrates an example configuration for using asmartphone to obtain a reflection spectrum. This example uses asmartphone 300 that includes a camera 302 (image sensor) and an LED 304(e.g., a white-light LED intended for flash photography) that is used asthe light source. As shown, the smartphone 300 is removably mounted to afixture that includes a pinhole 308, a collimating lens 310, an opening312 over which a PC 314 can be placed, a mirror 316, a cylindrical lens318, and a diffraction grating 320. Light from the LED 304 passesthrough the pinhole 308 and the collimating lens 310 to reach the PC314. The light reflected from the PC 314 will be primarily theresonantly reflected wavelengths. The reflected light from the PC 314 isreflected by the mirror 316 so that it passes through the cylindricallens 318 and diffraction grating 320, which disperses the reflectedlight into spatially-separated wavelength components that are receivedby the camera 302. This approach results in a peak in the reflectedspectrum, rather than a dip in the transmitted spectrum, which could beeasier to measure in the presence of ambient light.

8. Alternative Optical Assay Media

Described above are embodiments in which a PC is used for label-freedetection. In other embodiments, label-free detection of biomolecularassays may be achieved using other types of optical assay media. Forexample, the optical assay medium could include any detection surfacethat produces a distinct wavelength spectrum when illuminated by abroadband light source could be used in place of the PC. Further, thesmartphone could be used to measure shifts in the reflected ortransmitted spectra that occurs as a result of adsorption of biomaterialon the detection surface. Alternative detection surfaces can includesurface plasmon resonance (SPR) biosensors, resonant waveguide gratingbiosensors, zero mode waveguide surfaces, metal film over nanoparticle(MFON) surfaces, and many others.

In still other embodiments, the optical assay medium could be configuredto perform biomolecular assays with label-based detection. Suchlabel-based biomolecular assays could include, for example, opticalabsorption assays, surface-based fluorescence assays, solution-basedfluorescence assays, fluorescence polarization assays, and assays thatuse surface-enhance Raman scattering (SERS). These assay types aredescribed in more detail below.

a. Optical Absorption Assays

In optical absorption assays, the presence of an analyte in a testsample results in the generation of a colored product. The concentrationof colored product indicates the concentration of the analyte. Theconcentration of colored product is determined by measuring the opticaldensity of the test sample by illuminating the test sample with abroadband light source and measuring the decreased light intensitytransmitted through the sample for the absorption wavelength of thecolored product. Thus, the transmitted spectrum will have an absorptionfeature related to absorption of light by the colored product.

Enzyme-linked immunosorbent assays (ELISA) assays are a class of opticalabsorption assays. Briefly, a solid surface (such as the surface of amicroplate well) is prepared with an antibody that selectively capturesan analyte from a test sample. After capture of the analyte, a secondaryantibody (recognizing a different location on the analyte than thecapture antibody) is applied to the surface. The secondary antibody islinked to an enzyme, and a substrate to that enzyme is introduced to theliquid solution, so that the enzyme-substrate interaction generatescolored products. In this process, the enzyme is not consumed, so theamount of colored product will accumulate the longer the interaction isallowed to occur. Based upon this basic principle, several distincttypes of ELISA assays have been developed (indirect ELISA, sandwichELISA, competitive ELISA), which share the detection method ofquantifying the optical density of the liquid sample to determine theconcentration of colored reaction products. ELISA assays are performedin a transparent container of known dimensions (a “cuvette”), bymeasuring the intensity of light transmission through the cuvette atspecific wavelengths.

FIG. 13 is a schematic diagram of how a smartphone-based spectrometercould be used to measure the optical density of a liquid sample placedin the optical path between a broadband light source, such as anincandescent light bulb or an LED, and a diffraction grating. Thediffraction grating disperses the transmitted light intospatially-separated wavelength components that are received by the imagesensor (CCD) of a smartphone. A dip in the transmission spectrum isrelated to absorption of light in the liquid sample and can be used tomeasure the optical density of the liquid sample. As shown, the opticalassay medium includes a glass cuvette that contains a composition forperforming an ELISA assay. It is to be understood, however, that thearrangement shown in FIG. 13 could also be used for other opticalabsorption assays as well.

b. Surface-Based Fluorescence Assays

Fluorophores are often attached to biomolecular or cellular analytes toaid in their detection. When analytes labeled with fluorophores areimmobilized upon a solid substrate, the surface density of the labeledanalyte can be measured by illuminating with a laser and collecting thefluorescence emission. An example smartphone-based detection system formeasuring the fluorescence emission is shown in FIG. 14. In thisexample, the fluorescently-labeled analyte is immobilized on a PC,though other solid substrates (such as a glass slide) could be used. ThePC is illuminated with a laser or other narrowband source with awavelength that excites the fluorophore so as to cause fluorescenceemission. The fluorescence emission is collected by a lens and directedto a diffraction grating. The diffraction grating disperses thetransmitted light into spatially-separated wavelength components thatare received by the image sensor (CCD) of a smartphone. A peak in theemission spectrum can be used to measure the surface density of thelabeled analyte. As shown, an emission filter is used to block the laserwavelength from being received by the image sensor of the smartphone.Alternatively, the laser wavelength may be spatially separated from thewavelength of the fluorescence emission by the diffraction grating andselectively blocked.

Certain solid substrates are capable of enhancing the amount offluorescence emission detected through the mechanisms of enhancedexcitation and/or enhanced extraction. Examples include PC surfaces (asshown in FIG. 14), roughened metal surfaces, zero-mode waveguides, andsurfaces exhibiting surface plasmon resonances. In this regard, PCsurfaces have been demonstrated as a means for enhancing the detectionsensitivity and resolution for assays that use a fluorescent tag toquantify the concentration of an analyte protein molecule in a liquidtest sample. PC fluorescent excitation enhancement is obtained bydesigning the PC structure to provide an optical resonance at the samewavelength as a laser that is used to excite a particular fluorescentdye. Compared to illumination of a fluorophore by a laser on an ordinaryglass surface, illumination of a PC by a laser at the resonant couplingcondition establishes an electromagnetic standing wave that is confinedto the PC surface with a magnitude that is 30-50 times greater than theillumination source. The enhanced electric field extends into the medium(air or water) that is adjacent to the PC, where its intensity decaysexponentially to form a ˜100 nm deep evanescent field region. Theresonant enhancement may be switched on by illuminating the PC with acollimated laser at the resonant coupling angle, and may be switched offby illuminating at a different incident angle.

PC surfaces also offer a second enhancement mechanism called “enhancedextraction.” Enhanced extraction is obtained by designing the PC toprovide a second optical resonance at the wavelength of fluorescenceemission, resulting in a greater proportion of emitted photons beingdirected near-normal to the PC surface, where they can be gatheredefficiently by a detection system. The effects of enhanced excitationand enhanced extraction multiply to result in ˜500× overall increase inmeasured fluorescent intensity on an appropriately designed PC, comparedto detection of the same analyte on an unpatterned glass surface.

c. Solution-Based Fluorescence Assays

In addition to surface-based fluorescence assays, a smartphone-baseddetection system could be used to detect fluorescence emission fromfluorescently-labeled analytes in solution. The configuration could besimilar to that shown in FIG. 14 but with the solid substrate beingsubstituted with a transparent liquid container that contains thefluorescently-labeled analytes. The transparent liquid container couldbe, for example, a cuvette or a microfluidic channel with a moving flowof fluorescent-labeled analytes. The system could be used to performfluorescent resonant energy transfer (FRET) assays in which the bindingof biomolecules in solution generates an increase in fluorescenceemission from one type of fluorophore (such as an “acceptor”fluorophore) and simultaneous decrease in fluorescence emission fromanother type of fluorophore (such as a “donor” fluorophore). The systemcould also be used to detect fluorescence from “molecular beacon”probes, quantum dots, and fluorescent microspheres that are floating insolution.

d. Fluorescence Polarization Assays

Fluorescence polarization (FP) is a homogeneous (liquid-based) assay inwhich the “polarization” of fluorescence emitted by a fluorophore ismeasured. The “polarization” (P) is defined byP=(I_(∥)−I_(⊥))/(I_(∥)+I_(⊥)), where I_(∥) and I_(⊥) represent thefluorescence intensity obtained with the polarizing filter in front ofthe sensor oriented parallel or perpendicular to the fluorescenceexcitation polarization. Due to the short (1-20 ns) time delay betweenexcitation and fluorescence emission (called the fluorescent lifetime),larger molecules, which rotate more slowly in solution than smallermolecules, will have a polarization that is closer to that of theexcitation. Briefly, two measurements of fluorescence intensity measuredthrough a linear polarizing filter rotated to orthogonal orientationsare used to determine the polarization. When a small molecule thatrotates rapidly is bound to a larger molecule, the rotation rate isdecreased, resulting in an increase in polarization of the fluorescenceemission.

An example smartphone-based detection system for measuring thepolarization fluorescence emission is shown in FIG. 15. A liquid testsample in a transparent container is placed in the optical path betweena laser (excitation) and the smartphone. The light entering the liquidsample is linearly polarized by passing through a polarizing filter, orby using a linearly polarized laser source. A second linearly polarizedfilter is placed on the distal end of the sample which may be switchedbetween two polarization states. Fluorescence emission is collected by alens and directed to a diffraction grating. The diffraction gratingdisperses the transmitted light into spatially-separated wavelengthcomponents that are received by the image sensor (CCD) of a smartphone.Measurements of fluorescence intensity are taken with the switchablepolarization filter oriented in alignment with the first linearpolarizer and orthogonal to the first linear polarizer.

e. Surface-Enhanced Raman Scattering (SERS)

In SERS assays, the analyte binds to Raman reporter molecules that areon a nanostructured surface that is capable of enhancing surfaceelectric fields from an incident laser source. The surface-enhancementcan increase the intensity of Raman scattering by many orders ofmagnitude. A smartphone-based detection system for measuring the Ramanscattering can be similar to that shown in FIG. 14, but with a SERSsurface taking the place of the PC and Raman reporter molecules takingthe place of the fluorophores. Alternatively, a reflection configurationcould be used.

9. Example Multimode Instrument

A smartphone could be coupled to an instrument that is capable ofperforming multiple different types of biomolecular assays, such as anyof the assay formats described above. FIG. 16 illustrates an example inwhich a multimode instrument 400 is coupled to a smartphone 402. Thesmartphone 402 includes an LED 404 and a camera 406. The camera 406includes an image sensor, such as a CCD. The instrument 400 includes asample chamber 408 for receiving an optical assay medium. The opticalassay medium could include a PC, a cuvette, or other componentsdepending on the type of optical assay being performed. The samplechamber 408 may include a door 410 that prevents stray light fromentering.

The optical assay medium may be positioned over a detection head 412 inthe sample chamber 408. The instrument 400 may include an optical outputpath for receiving an optical output from the optical assay medium inthe sample chamber 408 via the detection head 412. The optical outputpath may include a multimode fiber 414 that directs light from thedetection head 412 to a cylindrical lens 416. The optical output pathmay further include a wavelength-dispersive element, such as adiffraction grating 418, that is configured to disperse the opticaloutput into spatially-separated wavelength components. The opticaloutput path may also include other optical components, such ascollimating lenses, filters, and polarizers.

The instrument 400 can include a mount for removably mounting thesmartphone 402 in a working position such that the camera 406 isoptically coupled to the optical path, for example, in a predeterminedposition relative to the diffraction grating 418. In this workingposition, the camera 406 can receive at least a portion of the dispersedoptical output such that different locations are received at differentlocations on the image sensor.

The instrument 400 may also include an input optical path for directinglight from a light source to the optical assay medium in the samplechamber 408, for example, through the detection head 412. In someinstances, the LED 404 on the smartphone 402 could be used as the lightsource. To use the LED 404 as the light source, the input optical pathmay include a collimating lens 420 that receives light from the LED 404when the smartphone is mounted to the instrument 400 in the workingposition. The input optical path may further include a multimode fiber422 that directs the light from the collimating lens 420 to thedetection head 412. The input optical path may also include otheroptical components, such as collimating lenses, filters, and polarizers.

The instrument 400 may also include an additional input optical paththat directs light form an internal light source, such as a laser 424,to the optical assay medium in the sample chamber 408. The additionalinput optical path may include a multimode optical fiber 426, as well ascollimating lenses, filters, polarizers, or other optical components.

For label-free assays (e.g., using a PC) and optical absorption assays(e.g., ELISA assays), the LED 404 may be used as the light source. Forfluorescence-based assays, laser 424 may be used as the light source,and a fixed linear polarizer 428 may be included in the input opticalpath. An emission filter 430 may also be included in the output opticalpath to filter out the wavelength of the laser 424. For fluorescencepolarization assays, a rotatable linear polarizer 432 may also beincluded in the output optical path.

The sample chamber 408 may be able to accommodate both homogeneous andheterogeneous assays. In some examples, homogeneous assays (such asELISA, FRET, and FP) may be performed in a transparent 1.5 mL disposablecuvette that is inserted into the sample chamber 408 for one-at-a-timeanalysis. In some examples, heterogeneous assays (PC biosensor,surface-based FRET) may be performed in a cartridge containing 16independent wells that be measured in series by sliding the cartridge infixed increments across the detection head 412. For enhancement offluorescence emission, a PC may be incorporated into the internalsurface of the cuvette (for homogeneous assays) or the surface of amicroscope slide (for heterogeneous assays).

The smartphone 402 can run an application for use with instrument 400.The application may be used to perform such functions as systemcalibration (including wavelength and intensity calibration), promptinga user through assay steps, gathering optical data, performing imageprocessing, and reporting results. The application can lead an untraineduser through the process of performing the assay correctly and canreduce the likelihood of user error leading to false positive or falsenegative assay results.

The application could also combine assay results with other sources ofsensor data from the smartphone, such as images, video, audiorecordings, location, and date/time. The application may be able tosecurely communicate results to user-specified servers, for example, todeliver results to a patient's physician. The results could also becollected in a database for additional analysis, such as developingstatistics or identifying disease outbreaks.

10. Conclusion

Example embodiments have been described. It is to be understood,however, that variations of these embodiments, as well as additionalembodiments, are possible within the scope of the claims set forthbelow.

What is claimed is:
 1. A system, comprising: a mobile computing device,wherein the mobile computing device includes an image sensor, aprocessor, and a memory that stores program instructions; an opticalinstrument, comprising: a sample chamber for receiving an optical assaymedium configured to perform a biomolecular assay, wherein the samplechamber comprises a door that prevents stray light from entering,wherein the optical assay medium comprises at least one fluorophore; alight source; an input optical path for directing light from the lightsource to the optical assay medium in the sample chamber, wherein theinput optical path comprises a first multimode fiber; an output opticalpath for receiving an optical output from the optical assay medium inthe sample chamber, wherein the output optical path comprises a secondmultimode fiber and a wavelength-dispersive element configured todisperse the optical output into spatially-separated wavelengthcomponents; and a mount for mounting the mobile computing device to theinstrument in a fixed position relative to the wavelength-dispersiveelement, wherein in the fixed position the image sensor of the mobilecomputing device is optically coupled to the output optical path suchthat the image sensor receives at least a portion of the dispersedoptical output and different wavelength components are received atdifferent locations on the image sensor, wherein the programinstructions stored in the memory are executable by the processor tocause the mobile computing device to perform functions, the functionscomprising: using the image sensor to obtain at least one image of theportion of the dispersed optical output; and determining a wavelengthspectrum of the optical output based on the at least one image.
 2. Thesystem of claim 1, wherein the light source is a laser.
 3. The system ofclaim 1, wherein the optical output comprises a fluorescence emissionfrom the at least one fluorophore excited by light from the lightsource.
 4. The system of claim 3, wherein an intensity of thefluorescence emission is indicative of a result of the biomolecularassay.
 5. The system of claim 3, wherein a polarization of thefluorescence emission is indicative of a result of the biomolecularassay.
 6. The system of claim 1, wherein the at least one fluorophorecomprises a donor fluorophore and an acceptor fluorophore.
 7. The systemof claim 6, wherein the optical output comprises a fluorescence emissionfrom the donor fluorophore and/or acceptor fluorophore.
 8. The system ofclaim 1, wherein the wavelength-dispersive element is a diffractiongrating.
 9. The system of claim 1, wherein in the fixed position a userinterface of the mobile computing device is accessible.
 10. The systemof claim 1, wherein the mobile computing device is a smartphone.
 11. Thesystem of claim 1, wherein the mobile computing device further includesa display and wherein the functions further comprise: displaying anindication of the wavelength spectrum of the optical output on thedisplay.
 12. The system of claim 1, wherein the mobile computing devicefurther includes a display and wherein the functions further comprise:determining a result of a biomolecular assay based on the wavelengthspectrum of the optical output; and displaying an indication of theresult on the display.
 13. The system of claim 1, wherein the mount isconfigured to removably mount the mobile computing device to theinstrument in a fixed position relative to the wavelength-dispersiveelement.